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Automatic recognition of fingerspelled words in British Sign Language

By S. Liwicki and M. Everingham


We investigate the problem of recognizing words from\ud video, fingerspelled using the British Sign Language (BSL)\ud fingerspelling alphabet. This is a challenging task since the\ud BSL alphabet involves both hands occluding each other, and\ud contains signs which are ambiguous from the observer’s\ud viewpoint. The main contributions of our work include:\ud (i) recognition based on hand shape alone, not requiring\ud motion cues; (ii) robust visual features for hand shape\ud recognition; (iii) scalability to large lexicon recognition\ud with no re-training.\ud We report results on a dataset of 1,000 low quality webcam\ud videos of 100 words. The proposed method achieves a\ud word recognition accuracy of 98.9%

Year: 2009
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